Navigating a website using visual analytics and a dynamic data source

ABSTRACT

Embodiments of the present invention disclose a method, computer program product, and system for identifying relevant content in a social media website. A social media site is mined for data and that data is stored as a data set. The data set is identified using a computer. A plurality of electronic records of the data set are received, wherein the electronic records are a result of the data mining. A plurality of ontologies is generated based on the electronic records and a subset of the plurality of ontologies is displayed on a user device. A user input is recorded as a user record and the set of ontologies that is displayed is modified.

BACKGROUND

The present invention relates generally to the field of social media,and more particularly to analytic visualization of a website.

Many websites contain social content, for example, comments, forums,discussions, or feeds. The issue with many social websites is thatnavigating the website's content is quite cumbersome. There are manypieces of content that may be in different locations that take time tobrowse or search for. This content often needs to be accesses usinghierarchies of information, or links provided by others, browsing withinforums, communities, reading lots of entries.

To navigate, websites have menus or filters, lists of most popular, mostread, new feeds, or search may be used in order to let people find whatis interesting on a website. The disadvantage of menus is that thecontent is mostly static and that every element in the menu has the samevisual treatment, and each of the menu items have the same importance.Also, menu items are pre-determined and might not offer the right textto identify the content of interest. For example, using most read, mostviewed, or most popular are often good starting-points, but thedisadvantage is that the user cannot find information that might be inthe lower percentile of popularity, causing users to find it difficultto engage with desired content, which may lead to disuse of the website.The disadvantage of search is that the user has to know where they areinterested in, it is using memory as starting-point and not recognition.

SUMMARY

Embodiments of the present invention disclose a method, computer programproduct, and system for identifying relevant content in a social mediawebsite. A social media site is mined for data and that data is storedas a data set. The data set is identified using a computer. A pluralityof electronic records of the data set are received, wherein theelectronic records are a result of the data mining. A plurality ofontologies is generated based on the electronic records and a subset ofthe plurality of ontologies is displayed on a user device. A user inputis recorded as a user record and the set of ontologies that is displayedis modified.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

FIG. 1 is a functional block diagram illustrating a distributed dataprocessing environment, in accordance with an embodiment of the presentinvention.

FIG. 2 is a functional block diagram illustrating components of anapplication running on a computing device of FIG. 1, in accordance withan embodiment of the present invention.

FIG. 3 is a flowchart depicting operational steps of an applicationreceiving, analyzing, and displaying data, in accordance with anembodiment of the present invention.

FIG. 4 is an illustrative depiction of an application display, inaccordance with an embodiment of the present invention.

FIG. 5 depicts a block diagram of components of the computing device andserver, in accordance with an embodiment of the present invention.

DETAILED DESCRIPTION

The present invention may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

Many websites contain social content, like comments, forums,discussions, and twitter feeds. The issue with many social websites isthat navigating the website's content is quite cumbersome. There aremany pieces of interesting content that the user needs to discover. Thisinteresting content often needs to be found by using hierarchies ofinformation, or links provided by others, browsing within forums,communities, reading lots of entries, etc. Social media may beintimidating to new users that have no experience and users may belooking for relevant information regarding a topic of interest asopposed to pure social interaction.

Embodiments of the invention will now be described in detail inreference to the Figures. FIG. 1 is a functional block diagramillustrating a distributed data processing environment, generallydesignated 100, in accordance with an embodiment of the presentinvention.

Distributed data processing environment 100 includes server 110 andcomputing device 130, all interconnected over network 150.

Network 150 may include permanent connections, such as wire or fiberoptic cables, or temporary connections made through telephone orwireless communications. Network 150 may represent a worldwidecollection of networks and gateways, such as the Internet, that usevarious protocols to communicate with one another, such as LightweightDirectory Access Protocol (LDAP), Transport Control Protocol/InternetProtocol (TCP/IP), Hypertext Transport Protocol (HTTP), WirelessApplication Protocol (WAP), etc. Network 150 may also include a numberof different types of networks, such as, for example, an intranet, alocal area network (LAN), or a wide area network (WAN).

Each of server 110 and computing device 130 may be a laptop computer,tablet computer, netbook computer, personal computer (PC), desktopcomputer, smart phone, or any programmable electronic device capable ofan exchange of data packets with other electronic devices, for example,through a network adapter, in accordance with an embodiment of theinvention, and which may be described generally with respect to FIG. 5below.

Server 110 may operation generally to send and receive data over network150. Server 110 may also receive data from a client in the form of a setof data mined electronic records. Server 110 includes data store 120that may index received electronic records to be communicated tocomputing device 130, in accordance with an embodiment of the invention.

Computing device 130 may operate generally to receive data, analyzedata, and display results. Computing device 130 may communicate withserver 110 via network 150. Computing device 130 includes ontologyapplication 140, as described in greater detail below, with reference toFIG. 2. In various embodiments of the invention, ontology application140 operates generally to receive input from a user, display data in agraphical user interface, or “GUI”, or communicate over a network, forexample a web browser.

In an embodiment of the invention ontology application 140 may receive,from data store 120 via server 110, a data set of electronic recordsfrom a social media website, via computing device 130. Ontologyapplication 140 may analyze the data set for similar electronic recordsand generate topical hierarchies, or ontologies, for variously similarelectronic records. In one embodiment semantic analysis may be used todetermine similarity in electronic records and generate ontologies basedon those semantic similarities. Other ontology generating techniques maybe used and semantic analysis is merely an example of one technique.

FIG. 2 is a functional block diagram illustrating components of anontology application 140 running on computing device 130 of FIG. 1, inaccordance with an embodiment of the present invention. Ontologyapplication 140 includes receiving module 210, analytics module 220,ontology module 230, and display module 240, denoted generally asenvironment 200.

In an embodiment of the invention. Receiving module 210 may receive adata set of electronic records. In various embodiments, an electronicrecord may be a user input, an electronic comment, an electronic review,an electronic rating, an electronic description, or a social mediaposting. Receiving module 210 may also receive user input in the form ofontology selections, described below. Receiving module 210 maycommunicate the electronic records to analytics module 220.

Analytics module 220 may act generally to receive electronic records,analyze electronic records in order to determine similarities, generateontologies based on those similarities, and communicate ontologies toontology module 230. Analytics module 220 may receive electronic recordsfrom receiving module 210 and store the electronic records in a datastore in memory. Analytics module 220 may perform an analysis of thereceived electronic records in order to determine topical similarities.This may be performed by various methods in the art, for example,semantic analysis of the textual data in the electronic records in orderto determine corresponding categories or ontologies. The number ofelectronic records associated with an ontology may also be recorded byanalytics module 220. Generated ontologies and the corresponding numberof electronic records may be communicated by analytics module 220 toontology module 230.

Ontology module 230 may act generally to receive ontologies fromanalytics module 220. Ontology module 230 may analyze the number ofelectronic records associated with each ontology and list theontologies, for example, from the ontology with the greatest number ofassociated electronic records to the ontology with the least number ofassociated electronic records. Ontology module may generate a subset ofontologies where the subset of ontologies includes the ontologies withthe most associated electronic records. The number of ontologies in thesubset of ontologies may be predetermined by a user or developer.Ontology module 230 may communicate the subset of ontologies to displaymodule 240.

Display module 240 may act generally to receive a subset of ontologies,determine a corresponding size value of each of the ontologies in thesubset of ontologies, display the ontologies in the subset ofontologies, for example via a GUI, and receive user input based on anontology selection.

In an embodiment of the invention, display module 240 may receive asubset of ontologies and a number for each ontology within the subset ofontologies, or “popularity value.” A popularity value for an associatedontology may be based on the number of electronic records associatedwith that ontology from the analysis described above by ontology module230. Display module 240 may analyze the popularity value and generate a“display size value.” A display size value may represent the size anontology will encompass in a GUI. For example, display module 240receives three ontologies “music,” “sports,” and “games.” Music may havea corresponding popularity value of 10 and sports and games may havepopularity values of 5. Display module 240 may display ontologies music,sports, and games where music will take up half of the display andsports and games will take of a quarter of the display each.

In an embodiment of the invention, display module 240 may receive anelectronic input from a user. The user input may correspond to anontology selection of an ontology displayed via the GUI. Display module240 may communicate the user selection to ontology module 230. Ontologymodule 230 may modify the popularity value of the user selected ontologyand update the order of the list of ontologies based on the newpopularity value of the user selected ontology. Based on the updatedlist of ontologies, ontology module 230 may communicate a new subset ofontologies to display module 240. Display module 240 may calculate newdisplay size values for the new set of ontologies received from ontologymodule 230 and update the size of the ontologies in the GUI.

In another embodiment of the invention, display module 240 maycommunicate the ontology selection to analytics module 220 and analyticsmodule 220 may communicate, to display module 240, the electronicrecords associated with the user selected ontology. Display module 240may display, via the GUI, the electronic comments, reviews, ratings,descriptions, and/or social media postings associated with the selectedontology. The GUI may contain various interactive elements as describedbelow, in reference to FIG. 4, allowing a user to navigate through oneor more ontologies and the associated electronic records.

In various embodiments of the invention, the popularity valuesassociated with ontologies may be modified based on a user's selectionhistory or electronic records generated by a user associated with anaccount or “profile history”. Display module 240 may generate a profilehistory by recording user selections in a data store in memory andcommunicating the user selections to ontology module 230 as describedabove. In various embodiments a profile history may be generated byreceiving module 210. Receiving module 210 may receive a user name andpassword associated with a social media website, “profile information”.Receiving module 210 may communicate to data store 120 via network 150the social media website associated with received profile information.Receiving module 210 may receive electronic records from data store 120associated with the profile information social media website or “profilerecords.” Receiving module 210 may communicate profile records toanalytics module 220 to be process as described above.

FIG. 3 is a flowchart depicting operational steps of ontologyapplication 140 receiving, processing, and displaying data, inaccordance with an embodiment of the present invention. Now referring toFIGS. 1, 2, and 3, receiving module 210 receives a data set from datastore 120. The data may contain electronic records from data mining asocial media website or a profile history as described above in step310. Receiving module 210 communicates the data set to analytics module220. In step 320, analytics module 220 analyzes the received data set,for example, through semantic analysis, and generates ontologiescorresponding to similarities in the electronic records. Analytic module220 may record the number electronic records associated with eachgenerated ontology in a data store in memory. Analytics module 220communicates the generated ontologies to ontology module 230.

Ontology module 230 arranges the generated ontologies from theontologies with the most associated electronic records to the least andgenerates a subset of ontologies, in step 330, where the subsetrepresents the ontologies with the most associated electronic records.The number of electronic records associated with each ontology may bereceived by ontology module 230 in order to generate various subsets ofontologies, for example, a subset of ten ontologies with the highestnumber associated electronic records, or a subset of ten ontologies withthe lowest number of associated electronic records. A subset ofontologies is communicated to display module 240. By generating a subsetof ontologies for display, popular ontologies can be accessed by usersunfamiliar with a social media site. These ontologies may enable theuser to determine topics of interest.

Display module 240 assigns a popularity value to each ontology withinthe received subset of ontologies in step 340. The popularity value maybe used to organize the ontologies in a list. Display module 240generates a size value, in step 350, based on the popularity value. Thesize value may be, for example, the percentage of the area of the GUIdesignated by display module 240 that an ontology will occupy. Invarious embodiments, the higher size value may correspond with a greaterarea in the GUI occupied by an ontology. Display module 240 displays theontologies via a GUI in step 360. The ontologies may be displayed, forexample as boxes containing ontology labels or ontology labels in a wordmap.

Display module 240 receives an electronic input corresponding to a userselecting a displayed ontology in step 370. Display module 240communicates the user selected ontology to ontology module 230. Based onthe user selection, ontology module 230 modifies the selected ontologiespopularity value, in step 380. The change in popularity value may changethe position of the user selected ontology in the list of ontologiesstored in a data store in memory by ontology module 230. Also in step380, ontology module 230 may communicate the new popularity value todisplay module 240 and display module 240 may calculate a correspondingnew size value for the user selected ontology, as described above.Display module 240 modifies the size of the user selected ontology,based on the new calculated size value, and displays the modifiedontology in step 390.

FIG. 4 is an illustrative depiction of a GUI displayed by ontologyapplication 140, in accordance with an embodiment of the presentinvention. FIG. 4, referred to generally as display 400, is merely anexample of a display generated by display module 240 includingontologies 410, menu 420, and filters 430. Ontologies 410 also includemusic ontology 411. The size of ontologies 410 may be determined by thecorresponding calculated size value as described above. Display module240 may receive an electronic input corresponding, for example, to auser selecting music ontology 411 within ontologies 410. Display module240 may modify the size of music ontology 411 to increase or decreasethe percentage of the displayed area of ontologies 410 music ontology411 occupies.

Menu 420 may act generally as a selection tool in order to viewontologies based on specific electronic records. Menu 420 includes dropdown menu 421. For example, a user may make a selection from drop downmenu 421. The selection, for example, may be to return only ontologiesassociated with social media electronic comments. Display module 240 maydisplay ontologies with associated electronic comments, in response tothe user selection from drop down menu 421.

Filters 430 may act generally to allow the user to view other ontologiesthat may not have the highest popularity value. Filters 430 includesbuttons top 25% 431, bottom 25% 432, average 433 and custom 434. Filters430 represent merely an example of filters that can be applied toontologies generated by analytics module 220. For example, the user mayselect one of filters 430, for example, bottom 25% 432, and displaymodule 240 may display only ontologies that have the lowest associatedpopularity values. Various other methods of displaying ontologies mayinclude a word map (not shown), for example, the ontologies with thelargest size value may have the largest font size in the GUI display.

Referring now to FIG. 5 depicts a block diagram of components ofcomputing device 130 and server 110 of FIG. 1, in accordance with anembodiment of the present invention. It should be appreciated that FIG.5 provides only an illustration of one implementation and does not implyany limitations with regard to the environments in which differentembodiments may be implemented. Many modifications to the depictedenvironment may be made.

Computing device 130 and server 110 may include one or more processors502, one or more computer-readable RAMs 504, one or morecomputer-readable ROMs 506, one or more computer readable storage media508, device drivers 512, read/write drive or interface 514, networkadapter or interface 516, all interconnected over a communicationsfabric 518. Communications fabric 518 may be implemented with anyarchitecture designed for passing data and/or control informationbetween processors (such as microprocessors, communications and networkprocessors, etc.), system memory, peripheral devices, and any otherhardware components within a system.

One or more operating systems 510, and one or more application programs511, for example, ontology application 140, are stored on one or more ofthe computer readable storage media 508 for execution by one or more ofthe processors 502 via one or more of the respective RAMs 504 (whichtypically include cache memory). In the illustrated embodiment, each ofthe computer readable storage media 508 may be a magnetic disk storagedevice of an internal hard drive, CD-ROM, DVD, memory stick, magnetictape, magnetic disk, optical disk, a semiconductor storage device suchas RAM, ROM, EPROM, flash memory or any other computer-readable tangiblestorage device that can store a computer program and digitalinformation.

Computing device 130 and server 110 may also include a R/W drive orinterface 514 to read from and write to one or more portable computerreadable storage media 526. Application programs 511 on computing device130 and server 110 may be stored on one or more of the portable computerreadable storage media 526, read via the respective R/W drive orinterface 514 and loaded into the respective computer readable storagemedia 508.

Computing device 130 and server 110 may also include a network adapteror interface 516, such as a TCP/IP adapter card or wirelesscommunication adapter (such as a 4G wireless communication adapter usingOFDMA technology). Application programs 511 on computing device 130 andserver 110 may be downloaded to the computing device 130 from anexternal computer or external storage device via a network (for example,the Internet, a local area network or other wide area network orwireless network) and network adapter or interface 516. From the networkadapter or interface 516, the programs may be loaded onto computerreadable storage media 508. The network may comprise copper wires,optical fibers, wireless transmission, routers, firewalls, switches,gateway computers and/or edge servers.

Computing device 130 and server 110 may also include a display screen520, a keyboard or keypad 522, and a computer mouse or touchpad 524.Device drivers 512 interface to display screen 520 for imaging, tokeyboard or keypad 522, to computer mouse or touchpad 524, and/or todisplay screen 520 for pressure sensing of alphanumeric character entryand user selections. The device drivers 512, R/W drive or interface 514and network adapter or interface 516 may comprise hardware and software(stored on computer readable storage media 508 and/or ROM 506).

The programs described herein are identified based upon the applicationfor which they are implemented in a specific embodiment of theinvention. However, it should be appreciated that any particular programnomenclature herein is used merely for convenience, and thus theinvention should not be limited to use solely in any specificapplication identified and/or implied by such nomenclature.

Based on the foregoing, a computer system, method, and computer programproduct have been disclosed. However, numerous modifications andsubstitutions can be made without deviating from the scope of thepresent invention. Therefore, the present invention has been disclosedby way of example and not limitation.

What is claimed is:
 1. A method for identifying relevant content, themethod comprising: identifying a data set using a computer, the data setbeing stored on a data storage device accessible by the computer;receiving a plurality of electronic records of the data set, wherein theelectronic records further includes a set of electronic recordsresulting from data mining associated with social content on a pluralityof social websites; generating a plurality of ontologies correspondingwith one or more similarities associated with the plurality ofelectronic records, wherein the generated plurality of ontologies arebased on an analysis of social content text associated with the datamined from the plurality of social websites; generating a first subsetof ontologies of the plurality of ontologies for display on a user'sdevice based on a popularity value, wherein the popularity value isbased on a count of electronic records associated with the first subsetof ontologies; determining a display size value based on the popularityvalue, wherein the display size value is a percent of a display of theuser's device; displaying the first subset of ontologies based on thedisplay size value, wherein the first subset of ontologies is displayedon a word map on a graphic user interface; recording a user record in adata store in response to receiving a user input selection of one ormore of the subset of ontologies, wherein the user input selectionincludes a filter based on a range of levels associated with thepopularity value on the one or more of the subset of ontologies and amenu to view one or more of the subset of ontologies based on one ormore specific electronic records; and modifying, in real time, the firstsubset of ontologies for display on the user's device in response to theuser input selection, wherein the modified first set of ontologiesidentifies one or more topics of interest associated with the pluralityof electronic records, wherein the popularity value associated with themodified first set of ontologies is modified and a new display sizevalue is calculated for the modified first set of ontologies.
 2. Themethod of claim 1, wherein the plurality of electronic records includesone or more of: the user input; an electronic comment associated withthe plurality of ontologies; an electronic review record of theplurality of ontologies; an electronic rating record of the plurality ofontologies; an electronic description record of the plurality ofontologies; and a social media posting associated with the plurality ofontologies.
 3. The method of claim 1, wherein the identified data set isbased on a user profile.
 4. The method of claim 1, further comprises: inresponse to a user input, generating a subset of electronic records ofthe plurality of electronic records for display.
 5. The method of claim1, wherein the generated subset of ontologies is based on one or moreof: the generated plurality of ontologies with the most associatedelectronic records; and the generated ontologies with the leastassociated electronic records.
 6. A computer program product foridentifying relevant content, the computer program product comprising:one or more computer-readable storage media and program instructionsstored on the one or more computer-readable storage media, the programinstructions comprising: instructions to identify a data set using acomputer, the data set being stored on a data storage device accessibleby the computer; instructions to receive a plurality of electronicrecords of the data set, wherein the electronic records further includesa set of electronic records resulting from data mining associated withsocial content on a plurality of social websites; instructions togenerate a plurality of ontologies corresponding with one or moresimilarities associated with the plurality of electronic records,wherein the generated plurality of ontologies are based on an analysisof social content text associated with the data mined from the pluralityof social websites; instructions to generate a first subset ofontologies of the plurality of ontologies for display on a user's devicebased on a popularity value, wherein the popularity value is based on acount of electronic records associated with the first subset ofontologies; instructions to determine a display size value based on thepopularity value, wherein the display size value is a percent of adisplay of the user's device; instructions to display the first subsetof ontologies based on the display size value, wherein the first subsetof ontologies is displayed on a word map on a graphic user interface;instructions to record a user record in a data store in response toreceiving a user input selection of one or more of the subset ofontologies, wherein the user input selection includes a filter based ona range of levels associated with the popularity value on the one ormore of the subset of ontologies and a menu to view one or more of thesubset of ontologies based on one or more specific electronic records;and instructions to modify, in real time, the first subset of ontologiesfor display on the user's device in response to the user inputselection, wherein the modified first set of ontologies identifies oneor more topics of interest associated with the plurality of electronicrecords, wherein the popularity value associated with the modified firstset of ontologies is modified and a new display size value is calculatedfor the modified first set of ontologies.
 7. The program product ofclaim 6, wherein the plurality of electronic records includes one ormore of: the user input; an electronic comment associated with theplurality of ontologies; an electronic review record of the plurality ofontologies; an electronic rating record of the plurality of ontologies;an electronic description record of the plurality of ontologies; and asocial media posting associated with the plurality of ontologies.
 8. Theprogram product of claim 6, wherein the identified data set is based ona user profile.
 9. The program product of claim 6, further comprises: inresponse to a user input, program instructions to generate a subset ofelectronic records of the plurality of electronic records for display.10. The program product of claim 6, wherein the generated subset ofontologies is based on one or more of: the generated plurality ofontologies with the most associated electronic records; and thegenerated ontologies with the least associated electronic records.
 11. Acomputer system for identifying relevant content, the computer systemcomprising: one or more computer processors; one or morecomputer-readable storage media; program instructions stored on thecomputer-readable storage media for execution by at least one of the oneor more processors, the program instructions comprising: instructions toidentify a data set using a computer, the data set being stored on adata storage device accessible by the computer; instructions to receivea plurality of electronic records of the data set, wherein theelectronic records further includes a set of electronic recordsresulting from data mining associated with social content on a pluralityof social websites; instructions to generate a plurality of ontologiescorresponding with one or more similarities associated with theplurality of electronic records, wherein the generated plurality ofontologies are based on an analysis of social content text associatedwith the data mined from the plurality of social websites; instructionsto generate a first subset of ontologies of the plurality of ontologiesfor display on a user's device based on a popularity value, wherein thepopularity value is based on a count of electronic records associatedwith the first subset of ontologies; instructions to determine a displaysize value based on the popularity value, wherein the display size valueis a percent of a display of the user's device; instructions to displaythe first subset of ontologies based on the display size value, whereinthe first subset of ontologies is displayed on a word map on a graphicuser interface; instructions to record a user record in a data store inresponse to receiving a user input selection of one or more of thesubset of ontologies, wherein the user input selection includes a filterbased on a range of levels associated with the popularity value on theone or more of the subset of ontologies and a menu to view one or moreof the subset of ontologies based on one or more specific electronicrecords; and instructions to modify, in real time, the first subset ofontologies for display on the user's device in response to the userinput selection, wherein the modified first set of ontologies identifiesone or more topics of interest associated with the plurality ofelectronic records, wherein the popularity value associated with themodified first set of ontologies is modified and a new display sizevalue is calculated for the modified first set of ontologies.
 12. Thesystem of claim 11, wherein the plurality of electronic records includesone or more of: the user input; an electronic comment associated withthe plurality of ontologies; an electronic review record of theplurality of ontologies; an electronic rating record of the plurality ofontologies; an electronic description record of the plurality ofontologies; and a social media posting associated with the plurality ofontologies.
 13. The system of claim 11, wherein the identified data setis based on a user profile.
 14. The system of claim 11, furthercomprises: in response to a user input, program instructions to generatea subset of electronic records of the plurality of electronic recordsfor display.
 15. The system of claim 11, wherein the generated subset ofontologies is based on one or more of: the generated plurality ofontologies with the most associated electronic records; and thegenerated ontologies with the least associated electronic records.